• DocumentCode
    1828009
  • Title

    Ant Colony Optimization based PID for single area load frequency control

  • Author

    Omar, Murad ; Soliman, M. ; Abdel Ghany, A.M. ; Bendary, F.

  • Author_Institution
    Dept. of Electr. Eng., Benha Univ., Cairo, Egypt
  • fYear
    2013
  • fDate
    Aug. 31 2013-Sept. 2 2013
  • Firstpage
    119
  • Lastpage
    123
  • Abstract
    In this paper a novel Artificial Intelligence technique known as Ant Colony Optimization (ACO) is used for optimal tuning of PID controller for load frequency control. The system proposed here is a single area with reheat thermal system containing nonlinearities represented by Generation Rate Constraint (GRC), dead band and wide range of parameters. Three different cost functions have been suggested for tuning the PID controller. The closed loop response using these values of PID gains has been compared with Ziegler-Nichols (ZN) tuned one, the system has been tested for various load changes to reveal the effectiveness of the proposed technique.
  • Keywords
    ant colony optimisation; closed loop systems; control nonlinearities; frequency control; load regulation; optimal control; three-term control; ACO algorithm; GRC; PID gain values; ant colony optimization; artificial intelligence technique; closed loop response; control nonlinearities; cost functions; dead band; generation rate constraint; optimal PID controller tuning; parameter range; reheat thermal system; single-area load frequency control; Convergence; Tuning; Zinc; Load Frequency Control (LFC); PID Controller;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling, Identification & Control (ICMIC), 2013 Proceedings of International Conference on
  • Conference_Location
    Cairo
  • Print_ISBN
    978-0-9567157-3-9
  • Type

    conf

  • Filename
    6642203